A robust adaptive model predictive control framework for nonlinear uncertain systems

Summary In this article, we present a tube‐based framework for robust adaptive model predictive control (RAMPC) for nonlinear systems subject to parametric uncertainty and additive disturbances. Set‐membership estimation is used to provide accurate bounds on the parametric uncertainty, which are emp...

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Vydané v:	International journal of robust and nonlinear control Ročník 31; číslo 18; s. 8725 - 8749
Hlavní autori:	Köhler, Johannes, Kötting, Peter, Soloperto, Raffaele, Allgöwer, Frank, Müller, Matthias A.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Bognor Regis Wiley Subscription Services, Inc 01.12.2021
Predmet:	Adaptive control Algorithms constrained control Constraint modelling Disturbances Feasibility Liapunov functions Nonlinear control nonlinear model predictive control Nonlinear systems Parameter estimation Predictive control Robust control uncertain systems Uncertainty
ISSN:	1049-8923, 1099-1239
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